Artificial Intelligence in Computer Science: Trends, Applications, Challenges, and Future Directions
DOI: https://doi.org/10.5281/zenodo.20590690
Abstract
Artificial intelligence (AI) has become a central research and development area in computer science because it changes how software is designed, data is interpreted, systems are protected, and human-computer interaction is organised. This review examines AI as a computer science subject by connecting foundations in machine learning, deep learning, knowledge representation, generative models, reinforcement learning, graph learning and responsible AI. The paper follows a narrative review style supported by recent literature and synthesises AI applications across software engineering, cybersecurity, data mining, computer vision, natural language processing, cloud systems, robotics and education. The review argues that modern AI is not only a set of algorithms but a full socio-technical pipeline that includes data governance, model development, deployment, monitoring and regulation. The main findings show that AI brings high value through automation, prediction, personalisation and decision support, but also creates challenges related to bias, explainability, adversarial attacks, data privacy, hallucination, compute cost, reproducibility and skills gaps. The review concludes that future computer science research should move from accuracy-driven AI towards trustworthy, efficient, explainable and human-centred AI systems. This direction is especially important as large language models and foundation models enter software development, cyber defence, education and enterprise workflows. A strong AI curriculum should therefore combine technical skills with evaluation, security, ethics and governance
How to Cite
Sakshi Sharma, "Artificial Intelligence in Computer Science: Trends, Applications, Challenges, and Future Directions", Vol. 4, Issue 2, 21-05-2026, pp. 14-34. DOI: https://doi.org/10.5281/zenodo.20590690
